Chair of Computer Science II - Software Engineering

(Bachelor/Master/Praktikum) Unlocking the Secrets of Time Series Complexity



Embark on a captivating journey at the intersection of mathematics and computer science with our one-off project offering on time series complexity. In a world inundated with vast datasets, understanding the intricate patterns within time series data has never been more crucial. As a student in the realm of computer science, imagine the power of unraveling the hidden complexities of temporal data—gaining insights that can revolutionize industries, predict trends, and enhance decision-making processes. This project offers you the opportunity to delve into the heart of time series analysis, exploring existing complexity measures and pushing the boundaries by crafting a novel measure based on the function parameters of polynoms fitted to each sequence.


In this project, you will delve into the existing landscape of time series complexity measures, gaining a profound understanding of their strengths and limitations. Armed with this knowledge, you'll then develop a cutting-edge complexity measure grounded in the parameters of polynomial approximation. This novel approach promises to offer a more nuanced and accurate representation of time series intricacies, paving the way for enhanced predictive modeling and data-driven decision-making. The project doesn't stop at theory—extensive experimentation awaits, where you'll apply your developed measure to real-world datasets, validating its efficacy and pushing the boundaries of what's possible in the realm of time series analysis.

The best way to discuss details and priorities is in person. Talk to us or send us an e-mail!

We offer

  • Working in foundational and innovative research areas
  • Intensive supervision and creative freedom
  • Combination of theory, experimentation, und programming with flexible focus

    3-6 Months


    Michael Stenger, M.Sc.